Efficient semantic web service matching using common ontology

To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.

Knowledge Representation and Semantic Inference of Process Based on Ontology and Semantic Web Rule Language

The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of expert system.The application mode of ontology and semantic technology on the process parameters recommendation are mainly investigated.Firstly,the content about ontology,semantic web rule language(SWRL)rules and the relative inference engine are introduced.Then,the inference method about process based on ontology technology and the SWRL rule is proposed.The construction method of process ontology base and the writing criterion of SWRL rule are described later.Finally,the results of inference are obtained.The mode raised could offer the reference to the construction of process knowledge base as well as the expert system's reusable process rule library.

基于语义Web技术的Wiki系统研究与设计

Wiki是互联网新一代模式Web2.0的典型代表.本文通过对现有Wiki系统的分析,针对现有Wiki系统中知识结构不清晰的问题,提出了可以利用语义Web技术将Wiki设计成为一种知识本体呈现工具的思路,并在此基础上提出了一种基于语义Web技术的Wiki系统设计及实现方案.

Evaluation of Multistrategy Classifiers for Heterogeneous Ontology Matching On the Semantic Web

On the semantic web, data interoperability and ontology heterogeneity are becoming ever more important issues. To resolve these problems, multiple classification methods can be used to learn the matching between ontologies. The paper uses the general statistic classification method to discover category features in data instances and use the first-order learning algorithm FOIL to exploit the semantic relations among data instances. When using multistrategy learning approach, a central problem is the evaluation of multistrategy classifiers. The goal and the conditions of using multistrategy classifiers within ontology matching are different from the ones for general text classification. This paper describes the combination rule of multiple classifiers called the Best Outstanding Champion, which is suitable for heterogeneous ontology mapping. On the prediction results of individual methods, the method can well accumulate the correct matching of alone classifier. The experiments show that the approach achieves high accuracy on real-world domain.

Web Semantic and Ontology

Ontologies have become a popular research topic in many communities. In fact, ontology is a main component of this research;therefore, the definition, structure and the main operations and applications of ontology are provided. Web content consists mainly of distributed hypertext and hypermedia, and is accessed via a combination of keyword based search and link navigation. Hence, the ontology can provide a common vocabulary, and a grammar for publishing data, and can supply a semantic description of data which can be used to preserve the ontologies and keep them ready for inference. This paper provides basic concepts of semantic web, and defines the structure and the main applications of ontology.

Semantic analysis approach for construction of OWL ontology

A semantic analysis approach is proposed, by which semantic relationships between concepts are identified and defined, and then mapped or transformed to OWL （web ontology language） ontology. The most common abstractions （namely, inclusion, aggregation and association） and their implication in ontology are discussed; then the OWL implementation for three abstractions are analyzed and illustrated. Taxonomies, constraints on properties for each class, and the relations between taxonomies in OWL ontology are established after all the semantic relationships are identified and described. This research is the basis for the development of the ontology conceptual model （OCM） and the mapping from OCM to OWL ontology.

Heuristic web service composition method based on domain ontology

In order to realize automatic web service composition, a heuristic web service composition method based on domain ontology is proposed. First, this method integrates the domain ontology and the artificial intelligence （AI） planning algorithm. Then, it uses the domain ontology and its reasoning capability to infer the semantic relationship among parameters. Finally, it transforms the web service composition problem into the planning problem based on the AI planning heuristic algorithm. The preliminary experimental results show that the above method compensates for the lack of semantics in the previous AI planning method and it can satisfy the requirements of quality and efficiency of composition, thus generating composite web services according to customer requirements automatically and efficiently.

Bridge Ontology: A Multi-Ontologies-Based Approach for Semantic Annotation

Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies. Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies. Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem. The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation. The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration. Key words semantic web - bridge ontology - multi-ontologies - semantic annotation CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024). National Grand Fundamental Research 973 Program of China (2002CB312000), National Re-search Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: WANG Peng (1977-), male, Ph.D candidate, research direction: semantic web, ontology, and knowledge representation on the Web.

Fishery Web Service Composition Method Based on Ontology

Various fishery information systems have been developed in different times and on different platforms. Wet） service application composition is crucial in the sharing and integration of fishery data and information. In the present paper, a heuristic web service composition method based on fishery ontology is presented, and the proposed web services are described. Ontology reasoning capability was applied to generate a service composition graph. The heuristic function was introduced to reduce the searching space. The experimental results show that the algorithm used considers the services semantic similarity and adiusts web service composition plan by dynamically relying on the empirical data.

Construction of Domain Web Classification Ontology Based on Suggested Upper Merged Ontology

Aiming at the problem of merging heterogeneous semantic taxonomy emerged in Web information integration, a method of building Web classification ontology （WCO） has been proposed. A WCO that is logically consistent with the suggested upper merged ontology （SUMO） is defined, together with axioms needed to classify Web pages. WCO can be used as a foundation of merging heterogeneous semantic taxonomy, and could be used to support Web information integration and classification based Web information retrieval.

VuWiki:An Ontology-Based Semantic Wiki for Vulnerability Assessments

Three decades of vulnerability research have generated a complex and growing body of knowledge.The concept of vulnerability,as well as its implementation in vulnerability assessments,is used in various disciplines and contexts.Correspondingly,a multitude of ideas and frameworks about how to conceptualize and measure vulnerability exists.To provide a structured representation of vulnerability,we have set up an ontology-based semantic wiki for reviewing and representing vulnerability assessments(www.vuwiki.org).Based on a survey of 55 vulnerability assessment studies,we first developed an ontology as an explicit reference system for describing vulnerability assessments.The ontology was then implemented in a semantic wiki which allows for the classification and annotation of vulnerability assessment.The resulting semantic wiki,Vu Wiki,does not aim at‘‘synthesizing’’a holistic and overarching model of vulnerability,but at(1)providing—both scientists and practitioners—with a uniform ontology as a reference system;(2)providing easy and structured access to the knowledge field of vulnerability assessments with the possibility for any user to retrieve assessments using specific research criteria;and(3)serving as a collaborative knowledge platform that allows for the active participation of those generating and using the knowledge represented in the vulnerability wiki.

Application of Ontology in the Web Information Retrieval

In this paper,the research advances of ontology and its application are reviewed firstly.With the development of ontology technology,subject-oriented web information retrieval technology combining ontology has been becoming one of the hot scientific issues.The innovative method of the semantic web technology combined with the traditional information retrieval technology is put forward,and the related algorithm based on ontology for judging the relevancy with different topics is also represented,and has proved to be effective in given experiments.

Generalized Testability Scheme Modeling of Materiel System Based on Information Ontology

A mode of ontology-based information integration and management( OIIM) for testability scheme was proposed through expatiating on the connotation of the system testability scheme.Aiming at the complexity of influencing factors in optimal design procedure of the testability scheme, the information of concept entities,concept attributions and concept relationships was analyzed and extracted,and then the testability scheme information ontology( TSIO) was built and coded via web ontology language( OWL).Based on the information ontology, the generalized model for testability scheme( GMTS) was founded by defining transformation rules. The primary study shows that the mode of OIIM for testability scheme can make up the deficiencies in knowledge representation and reasoning existing in traditional information models,and achieve the information share and reuse. It provides the effectual model basis for the optimal design of the testability scheme.

General ontology learning framework

In order to reduce the costs of the ontology construction, a general ontology learning framework （GOLF） is developed. The key technologies of the GOLF including domain concepts extraction and semantic relationships between concepts and taxonomy automatic construction are proposed. At the same time ontology evaluation methods are also discussed. The experimental results show that this method produces better performance and it is applicable across different domains. By integrating several machine learning algorithms, this method suffers less ambiguity and can identify domain concepts and relations more accurately. By using generalized corpus WordNet and HowNet, this method is applicable across different domains. In addition, by obtaining source documents from the web on demand, the GOLF can produce up-to-date ontologies.

基于Wiki的信息服务研究

本文首先概述了Wiki及其产生背景,并将它与其他个性化工具进行了比较。接着归纳了实现Wiki个性化服务的操作技术与规范,提出引入语义网技术并分析了几种具有代表性的Wiki引擎。最后介绍了Wiki个性化信息服务在企业管理、教育和学术研究等领域的应用。

Rules-based object-relational databases ontology construction

To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

Implementation of Enterprises Interoperation Based on Ontology

The interoperation among enterprises in e-business could block the ambient semantic collaboration and cause a big problem since varying information descriptions and different data models may be used in different enterprises＇ information systems. Ontology is an important tool to overcome the above mentioned syntax and semantic misunderstanding problem. Our goal is to provide a user-friendly environment supporting syntax and neutral format data model for business information. In this paper, two scenarios are discussed and a unified description of data model is developed to solve the gap in interoperation through mapping from logical data of enterprise＇s information system. It provides the methods to realize the mapping among different types of data or information. First, database and other types of information are transformed into neutral format that are described by web ontology language （OWL）. Second, the neutral format can be mapped into the semantic entities and semantic linking through the process of extraction and annotation and added into ontology and then described in a standard format that makes the collaboration be understood easily.

New automated ontology mapping algorithm

A new algorithm for automated ontology mapping based on linguistic similarity and structure similarity is presented. First, the concept of WordNet is turned into a vector, then the similarity of two entities is calculated according to the cosine of the angle between the corresponding vectors. Secondly, based on the linguistic similarity, a weighted function and a sigmoid function can be used to combine the linguistic similarity and structure similarity to compute the similarity of an ontology. Experimental results show that the matching ratio can reach 63% to 70% and it can effectively accomplish the mapping between ontologies.

Context-driven reconciliation in ontology integration

In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the previous work about a context-based formalism-Context-SHOIQ （D ＋ ） DL, which is used for explicitly representing context of ontology by adopting the description logic and the category theory. The formalism is extended by adding four migration rules （InclusionRule, SelectionRule, PreferenceRule, and MappingRule）, that are used to specify what should be imported into the IntegrativeContext, and three related contextual integration operations of increasing interoperability （import, partial reconciliation, and full reconciliation）. While not exhaustive, the mechanism is sufficient for solving the five types of semantic irreconcilable problems that are discussed, and favors integration of ontologies from one context to another.